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JerryZhou54
2026-02-07 21:43:09 +00:00
parent 8140cb4460
commit 0df9934f4d
13 changed files with 514 additions and 120 deletions
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examples/inference/basic/basic_wan2_2_Fun.py
+14 -8
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@@ -10,12 +10,13 @@ def main():
# If a local path is provided, FastVideo will make a best effort
# attempt to identify the optimal arguments.
generator = VideoGenerator.from_pretrained(
"IRMChen/Wan2.1-Fun-1.3B-Control-Diffusers",
"weizhou03/Wan2.1-Fun-1.3B-InP-Diffusers",
# "IRMChen/Wan2.1-Fun-1.3B-Control-Diffusers",
# "alibaba-pai/Wan2.2-Fun-A14B-Control",
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
dit_cpu_offload=True, # DiT need to be offloaded for MoE
dit_cpu_offload=False, # DiT need to be offloaded for MoE
vae_cpu_offload=False,
text_encoder_cpu_offload=True,
# Set pin_cpu_memory to false if CPU RAM is limited and there're no frequent CPU-GPU transfer
@@ -23,14 +24,19 @@ def main():
# image_encoder_cpu_offload=False,
)
prompt = "一位年轻女性穿着一件粉色的连衣裙，裙子上有白色的装饰和粉色的纽扣。她的头发是紫色的，头上戴着一个红色的大蝴蝶结，显得非常可爱和精致。她还戴着一个红色的领结，整体造型充满了少女感和活力。她的表情温柔，双手轻轻交叉放在身前，姿态优雅。背景是简单的灰色，没有任何多余的装饰，使得人物更加突出。她的妆容清淡自然，突显了她的清新气质。整体画面给人一种甜美、梦幻的感觉，仿佛置身于童话世界中。"
negative_prompt = "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
# prompt = "一位年轻女性穿着一件粉色的连衣裙，裙子上有白色的装饰和粉色的纽扣。她的头发是紫色的，头上戴着一个红色的大蝴蝶结，显得非常可爱和精致。她还戴着一个红色的领结，整体造型充满了少女感和活力。她的表情温柔，双手轻轻交叉放在身前，姿态优雅。背景是简单的灰色，没有任何多余的装饰，使得人物更加突出。她的妆容清淡自然，突显了她的清新气质。整体画面给人一种甜美、梦幻的感觉，仿佛置身于童话世界中。"
# negative_prompt = "色调艳丽，过曝，静态，细节模糊不清，字幕，风格，作品，画作，画面，静止，整体发灰，最差质量，低质量，JPEG压缩残留，丑陋的，残缺的，多余的手指，画得不好的手部，画得不好的脸部，畸形的，毁容的，形态畸形的肢体，手指融合，静止不动的画面，杂乱的背景，三条腿，背景人很多，倒着走"
# prompt = "A young woman with beautiful, clear eyes and blonde hair stands in the forest, wearing a white dress and a crown. Her expression is serene, reminiscent of a movie star, with fair and youthful skin. Her brown long hair flows in the wind. The video quality is very high, with a clear view. High quality, masterpiece, best quality, high resolution, ultra-fine, fantastical."
# negative_prompt = "Twisted body, limb deformities, text captions, comic, static, ugly, error, messy code."
image_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/8.png"
control_video_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/pose.mp4"
video = generator.generate_video(prompt, negative_prompt=negative_prompt, image_path=image_path, video_path=control_video_path, output_path=OUTPUT_PATH, output_video_name=OUTPUT_NAME, save_video=True)
# image_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/8.png"
# control_video_path = "https://pai-aigc-photog.oss-cn-hangzhou.aliyuncs.com/wan_fun/asset_Wan2_2/v1.0/pose.mp4"
import json, os
with open("/mnt/weka/home/hao.zhang/wei/FastVideo/data/mixkit_i2v.jsonl", "r") as f:
prompt_image_pairs = json.load(f)
for d in prompt_image_pairs:
prompt = d["prompt"]
image_path = os.path.join("/mnt/weka/home/hao.zhang/wei/FastVideo", d["image_path"])
video = generator.generate_video(prompt, image_path=image_path, output_path=OUTPUT_PATH, output_video_name=OUTPUT_NAME, save_video=True)
if __name__ == "__main__":
main()
examples/inference/basic/basic_wan2_2_ti2v.py
+14 -2
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@@ -1,6 +1,6 @@
from fastvideo import VideoGenerator
OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v"
OUTPUT_PATH = "video_samples_wan2_2_5B_ti2v_720p_77"
def main():
# FastVideo will automatically use the optimal default arguments for the
# model.
@@ -12,17 +12,29 @@ def main():
# FastVideo will automatically handle distributed setup
num_gpus=1,
use_fsdp_inference=False, # set to True if GPU is out of memory
dit_cpu_offload=True,
dit_cpu_offload=False,
vae_cpu_offload=False,
text_encoder_cpu_offload=True,
pin_cpu_memory=True, # set to false if low CPU RAM or hit obscure "CUDA error: Invalid argument"
# image_encoder_cpu_offload=False,
)
import json, os
with open("/mnt/weka/home/hao.zhang/wei/FastVideo/data/mixkit_i2v_720p.jsonl", "r") as f:
prompt_image_pairs = json.load(f)
for d in prompt_image_pairs:
prompt = d["prompt"]
image_path = os.path.join("/mnt/weka/home/hao.zhang/wei/FastVideo", d["image_path"])
video = generator.generate_video(prompt, image_path=image_path, output_path=OUTPUT_PATH, output_video_name=OUTPUT_PATH, save_video=True, num_frames=77)
return
# I2V is triggered just by passing in an image_path argument
prompt = "Summer beach vacation style, a white cat wearing sunglasses sits on a surfboard. The fluffy-furred feline gazes directly at the camera with a relaxed expression. Blurred beach scenery forms the background featuring crystal-clear waters, distant green hills, and a blue sky dotted with white clouds. The cat assumes a naturally relaxed posture, as if savoring the sea breeze and warm sunlight. A close-up shot highlights the feline's intricate details and the refreshing atmosphere of the seaside."
image_path = "https://huggingface.co/datasets/YiYiXu/testing-images/resolve/main/wan_i2v_input.JPG"
# prompt = "In the midst of the joyous New Year's Eve celebration, the cheerful group of friends, their spirits lifted by the festivities, decides to immortalize the moment with a vibrant snapshot"
# image_path = "images/mixkit-a-cheerful-group-of-friends-celebrate-new-years-eve-and-51525.png"
video = generator.generate_video(prompt, output_path=OUTPUT_PATH, save_video=True, image_path=image_path)
return
# Generate another video with a different prompt, without reloading the
# model!